Predicting Breast Cancer Incidence Rates Among White and Black Women in the United States: An Application of FTS Model
International Journal of Statistical Distributions and Applications
Volume 3, Issue 4, December 2017, Pages: 103-112
Received: Mar. 10, 2017; Accepted: Mar. 29, 2017; Published: Nov. 28, 2017
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Farah Yasmeen, Department of Statistics, University of Karachi, Karachi, Pakistan
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Development of statistical model for cancer incidence trend predictions can provide a sound and accurate foundation for planning a comprehensive national strategy for optimal partitioning of research resources. Several studies in the past showed that that there are racial/ethnic disparities exist between breast cancer incidence rates among black and white women in the United States. Some of the studies also showed that the disparity in breast cancer incidence rates among white and black US women is widening, with relatively higher incidence rates among black women. In this paper, we apply functional time series (FTS) models on the age-specific breast cancer incidence rates for these two major groups of women in US, and forecast their age-incidence curves. The data are obtained from the Surveillance, Epidemiology and End Results (SEER) program of the United States. We use annual unadjusted breast cancer incidence rates from 1973 to 2013 in 5-year agegroups (15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45–49, 50–54, 55–59, 60–64, 65–69, 70–74, 75–79, 80–84 and 85+). Age-specific cancer incidence curves are obtained using nonparametric smoothing methods. The curves are then decomposed using functional data paradigm and we fit functional time series (FTS) models for each population of women separately. The smoothed incidence curves are then forecasted and prediction intervals are calculated. Fifteen-year forecasts indicate an overall increase in future breast cancer incidence rates for both groups of women. This increase appears to be faster among black women and relatively slower among the whites. The projections suggest a need for equal delivery of quality care to eliminate breast cancer disparities among the two major groups of women in US.
Breast Cancer, Cancer Incidence, Screening and Early Detection, Functional Time Series, Forecasts, Black and White Disparity
To cite this article
Farah Yasmeen, Predicting Breast Cancer Incidence Rates Among White and Black Women in the United States: An Application of FTS Model, International Journal of Statistical Distributions and Applications. Vol. 3, No. 4, 2017, pp. 103-112. doi: 10.11648/j.ijsd.20170304.17
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM, Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008, Int J Cancer. 127 (2010) 2893–917.
Cancer Treatment And Survivorship Statistics, 2016 CA: A Cancer Journal For Clinicians (2016)
Li CI, Malone KE, Daling JR. Differences in breast cancer stage, treatment, and survival by race and ethnicity, Arch Intern Med. 163(1) (2003) 49–56.
Chu KC, Lamar CA, Freeman HP. Racial disparities in breast carcinoma survival rates: separating factors that affect diagnosis from factors that affect treatment, Cancer, 97(11) (2003) 2853–2860.
Li CI, Malone KE, Daling JR. Differences in breast cancer hormone receptor status and histology by race and ethnicity among women 50 years of age and older, Cancer Epidemiology Biomarkers Prev.11(7) (2002) 601–607.
Hyndman R.J. and Ullah, M. S, Robust forecasting of mortality and fertility rates: A functional data approach. Computational Statistics & Data Analysis, 51 (2007) 4942 – 4956.
Erbas, B., Hyndman, R. J. and Gertig, D.M., Forecasting age-specific breast cancer mortality using functional data models. Statistics in Medicine, 26 (2007) 458-470.
Yasmeen, F., Hyndman, R. J. and Erbas, B., Forecasting age-related changes in breast cancer mortality among white and black US women: A functional data approach. Cancer Epidemiology, 34(5) (2010) 542-549.
Yasmeen, F., Coherent Forecasts of US Age-specific Breast Cancer Mortality, Donnish Journal of Cancer Research and Experimental Oncology, 1(1) (2015)001-008, http://
Yasmeen, F., Zaheer, S., Functional time series models to estimate future age specific breast cancer incidence rates for women in Karachi, Pakistan. J Health Sci,2(2014)213‑221.
Zaheer, S. and Yasmeen, F., Breast Cancer Incidence Rates in Karachi, Proceeding of 10th International Conference on Statistical Sciences (ISOSS), March 7-9, Lahore, Pakistan, 24 (2013) 71-78.
Yasmeen, F., Modeling Breast Cancer Incidence Rates: A Comparison between the Components of Functional Time Series (FTS) Model applied on Karachi (Pakistan) and US Data, Open Journal of Applied Sciences, 6(2016) 524-533.
Yasmeen, F. and Mughal, S .Functional Time Series Models and the APC Models: A Comparative Study on the Lung Cancer Incidence Rates in Denmark, Journal of US-China Medical Science, ISSN 1548-6648, USA, 11(3)(2014) 121-128.
Surveillance, Epidemiology, and End Results (SEER) Program. Delay-Adjusted Incidence database: "SEER Incidence Delay- Adjusted Rates, 9 Registries, 1975–2013". National Cancer Institute, DCCPS, Surveillance Research Program, Statistical Research and Applications Branch, released April based on the November 2015 SEER data submission.
Hyndman, R. J., Demography: Forecasting mortality, fertility, migration and population data, R. package, version 1.18, with contribution from Heather Booth, Leonie Tickle and John Maindonald(2014)(
Hyndman, R.J., Forecast: Forecasting functions of time series models, R. package, Version 7.1(2014) (
Hyndman R J and Shang H.L. Rainbow plots, bagplots and boxplots for functional data. J Comput Graph Stat, 19(1) (2010)29–45.
Jemal A, Clegg LX, Ward E, et al. Annual report to the nation on the status of cancer, 1975–2001, with a special feature regarding survival. Cancer. 101(1)(2004) 3–27.
Jemal A, Siegel R, Ward E. Cancer statistics, 2006. CA Cancer J Clin. 56(2) (2006) 106–130.
US Department of Health and Human Services. National Healthcare Disparities Report. US Department of Health and Human Services, Agency for Health Care Research and Quality; Rockville, MD: (2003).
Smigal C, Jemal A, Ward E, et al. Trends in breast cancer by race and ethnicity: update 2006. CA Cancer J Clin.56(3) (2006) 168–183.
Tammemagi CM, Nerenz D, Neslund-Dudas C, Feldkamp C, Nathanson D. Comorbidity and survival disparities among black and white patients with breast cancer. JAMA.294(14) (2005) 1765–1772.
Newman LA. Breast cancer in African-American women. Oncologist 10(1) (2005) 1–14.
Newman LA, Griffith KA, Jatoi I, Simon MS, Crowe JP, Colditz GA. Meta-analysis of survival in African American and white American patients with breast cancer: ethnicity compared with socioeconomic status. J ClinOncol. 24(9) (2006) 1342–1349.
Chlebowski RT, Chen Z, Anderson GL. Ethnicity and breast cancer: factors influencing differences in incidence and outcome. J Natl Cancer Inst. 97(6) (2005) 439–448.
Field TS, Buist DS, Doubeni C. Disparities and survival among breast cancer patients. J Natl Cancer InstMonogr 35(2005) 88–95.
DeSantis CE, Fedewa SA, Goding Sauer A, Kramer JL, Smith RA, Jemal A. Breast cancer statistics, 2015: Convergence of incidence rates between black and white women. CA Cancer J Clin., 66(1) (2016) 31-42.
Chu KC, Tarone RE, Brawley OW. Breast cancer trends of black women compared with white women. Arch Fam Med. 8(6) (1999) 521–528.
Cancer treatment and survivorship statistics, 2016, CA A Cancer Journal for Clinicians, (2016)
Atlanta: American Cancer Society; 2013. American Cancer Society. Breast Cancer Facts and Figures (2013).
Cooper K. Springhouse: Springhouse Corp, Pathophysiology Made Incredibly Easy. (1998).
Gallucci BB. Selected concepts of cancer as a disease: From the Greeks to 1900. OncolNurs Forum.12 (1985) 67–71.
Atlanta: American Cancer Society; 2009. American Cancer Society. Recommendations for the Early Detection of Cancer.
Edge S, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A, editors. 7th ed. New York: Springer AJCC Cancer Staging Manual (2010)347–69.
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